It is known that a prefilter, which is often used in a preprocess of video encoding, is effective for reducing block distortion, mosquito noise, or the like, accompanied with encoding, thereby improving the subjective image quality. The pass bandwidth (called “bandwidth” below) of the used prefilter is limited, so as to reduce noise included in an original image and improve the encoding efficiency. However, if the bandwidth is narrowed too much, the image quality is extremely degraded.
FIG. 7 shows an image processing method including a band limitation.
As shown in FIG. 7, in the image processing method including the band limitation, first, original image data B(1) is input, and is then converted into a frequency component I(1) (see step S100). The frequency component I(1) is subjected to a band limitation using a bandwidth r1 (0<r1<1), so that a frequency component (r1) is obtained (see step S101). The frequency component I(r1) is subjected to image transformation, thereby generating filtered image data B(r1) (see step S102).
When such image processing is applied to all frames of a video image by using the same bandwidth, image quality of each filtered frame is not equal because each frame has the individual frequency characteristics of the image. That is, an image having a large amount of low-frequency components has only a small difference from the original image, and thus degradation in the subjective and objective image qualities is small. However, in an image having a large amount of high-frequency components, edges or the like are smoothed and blurred, which extremely degrades subjective and objective image qualities.
As an objective image estimation value, for example, a PSNR (Peak Signal to Noise Ratio) is often used. With given signal level (S) and noise level (N), the PSNR is indicated by the following formula:PSNR=20×log10(S/N)
In a method for solving the above problem, subjective and objective image quality control is performed by means of a “round-robin” band limitation applied to each image.
FIG. 8 shows the structure of an optimum filtered image generating apparatus 100 for generating optimum filtered image data by performing a “round-robin” band limitation.
As shown in FIG. 8, the optimum filtered image generating apparatus 100 includes an original image data input unit 101, a frequency component analyzing unit 102, a bandwidth manual selecting unit 103, a band limitation unit 104, an image data generating unit 105, a PSNR computing unit 106, an image judgment unit 107, and an optimum band-limited image data output unit 108.
FIG. 9 shows an image processing method of generating optimum filtered image data by performing a “round-robin” band limitation, where the method is executed in the optimum filtered image generating apparatus 100 having the above structure.
In the optimum filtered image generating apparatus 100, first, original image data B(1) is input into the original image data input unit 101, and is then converted into a frequency component I(1) in the frequency component analyzing unit 102 (see step S200).
Next, in the bandwidth manual selecting unit 103, a provisional bandwidth r1 is manually selected (see step S201). Then, in the band limitation unit 104, the converted frequency component I(1) is subjected to a band limitation using the selected bandwidth r1, so as to obtain a frequency component I(r1) (see step S202).
Next, in the image data generating unit 105, the frequency component I(r1) is subjected to an image transformation, thereby generating image data B(r1) (see step S203). In the PSNR computing unit 106, the original image data B(1) is compared with the image data B(r1), so as to compute PSNR (r1) (indicated by “P(r1)” below) (see step S204).
In the image judgment unit 107, it is determined whether or not the computed P(r1) has a desired image quality (see step S205). If it has the desired image quality, the optimum band-limited image data output unit 108 outputs the image data B(r1) as optimum band-limited image data (i.e., optimum filtered image data) (see step S206).
However, it is rare that P(r1) obtained in the first processing turn has a desired image quality. When it does not have the desired image quality, the operation returns to the process (in step S201) performed by the bandwidth manual selecting unit 103, and a bandwidth (r2) is selected again so that the relevant band-limited image has a quality closer to the desired image quality. Then, band limitation, image generation, and PSNR computation are again performed similarly.
That is, the above-described operation is repeated N times until the desired image quality is obtained, and a bandwidth rN, which is obtained finally, is used as an optimum bandwidth for generating image data B(rN) by the optimum band-limited image data output unit 108. The generated image data B(rN) is output as optimum band-limited image data (i.e., optimum filtered image data) (see step S206).
However, in the above method, various video images and all frames which form thereof are subjected to filtering, the subjective or objective image quality of each obtained image signal is estimated, and the relevant operation is repeated in a “round-robin” manner until an equal image quality is obtained for all frames of the video images. In consideration of the required time and cost, when many images are processed, the above method is inappropriate and impracticable.
In order to solve the above problem, in a known technique (see Patent Document 1), image processing is performed by obtaining an optimum bandwidth based on the encoding data of a (video) image.
FIG. 10 shows the structure of an optimum filtered image generating apparatus 200 for generating optimum filtered image data by using encoding data.
As shown in FIG. 10, the optimum filtered image generating apparatus 200 includes an original image data input unit 201, a frequency component analyzing unit 202, an image data encoding unit 203, an optimum limited bandwidth determination unit 204, a band limitation unit 205, an image data generating unit 206, and an optimum band-limited image data output unit 207.
FIG. 11 shows an image processing method of generating optimum filtered image data by using encoding data, where the method is executed in the optimum filtered image generating apparatus 200 having the above structure.
In the optimum filtered image generating apparatus 200, first, original image data B(1) is input into the original image data input unit 201, and is then converted into a frequency component I(1) in the frequency component analyzing unit 202 (see step S300).
Next, in the image data encoding unit 203, the input original image data B(1) is encoded (see step S301). Based on the amount of codes obtained by the relevant encoding, an optimum bandwidth r1 is determined in the optimum limited bandwidth determination unit 204 (see step S302).
In the band limitation unit 205, the converted frequency component I(1) is subjected to a band limitation using the determined bandwidth r1, so as to obtain a frequency component I(r1) (see step S303). In the image data generating unit 206, the frequency component I(r1) is subjected to an image transformation, thereby generating image data B(r1) (see step S304).
Finally, the image data B(r1) is output as optimum band-limited image data (i.e., optimum filtered image data) from the optimum band-limited image data output unit 207 (see step S305).
Accordingly, in the conventional optimum filtered image generating apparatus 200 formed as shown in FIG. 10, after encoding is performed, an optimum bandwidth is determined based on encoding data obtained by the encoding. Therefore, optimum filtered image data is obtained without performing a repetitive operation as required in the optimum filtered image generating apparatus 100 formed as shown in FIG. 8.    Patent Document 1: Japanese Unexamined Patent Application, First Publication No. H06-225276.
Certainly, in accordance with the conventional optimum filtered image generating apparatus 200 formed as shown in FIG. 10, optimum filtered image data can be generated without performing a repetitive operation as required in the optimum filtered image generating apparatus 100 formed as shown in FIG. 8.
However, in the optimum filtered image generating apparatus 200 of FIG. 10, after encoding is performed, the optimum bandwidth is determined based on encoding data obtained by the encoding.
In such a method using encoding data, a band limitation process and an encoding process are inseparable. Therefore, even if the user would like to perform only a prefiltering process using the optimum bandwidth, encoding is also necessary. If encoding is also performed after the prefiltering process, encoding would be performed twice. In particular, if the image size is large, considerable processing time is required.
In consideration of the above, in order to optimize the bandwidth for the prefilter, it is preferable to employ a method which can simplify the relevant processing and can be voluntarily controlled using, for example, the PSNR (as a standard for estimating the objective image quality), in comparison with a method using encoding data (e.g., the amount of codes).